Tactical waveform software applications tend to suffer from inefficient implementations despite the availability of free and open source software (FOSS) profiling tools. It has been the overwhelming experience of the authors that tactical waveform developers rely too heavily on the optimization power of the compiler rather than on sound, high-performance software engineering practices including performance profiling. The suite of FOSS profiling tools is mature, vast, and growing. Valgrind, gprof, and perf are tools used to identify software deficiencies that diminish the performance and reliability of tactical waveforms and the radios that host them. These deficiencies can be categorized as application-level and microarchitectural deficiencies. Inefficient input/output (I/O), memory leaks, uninitialized variables, race conditions, and improperly prioritized threads are examples of application-level deficiencies. Inefficient instruction and data cache utilization, and severe branch prediction misses are examples of microarchitectural deficiencies. This paper presents a methodology to apply FOSS tools and techniques to improve the performance posture in both the application and microarchitectural domain. Furthermore, results of the approach are presented in a case study involving application of the proposed techniques against a real Department of Defense (DoD) tactical waveform application.

Emulation of tactical wireless networks in a laboratory environment provides a cost-effective solution for development tests and serves as a risk reduction for formal operational tests. However, laboratory-based emulation of tactical Mobile Ad Hoc Networks (MANETs) is particularly challenging due to the complex nature of the underlying environment. Unlike point to-point systems, emulation of MANETs requires the execution of multiple channels in parallel. Furthermore, tactical wireless channels are susceptible to impairments such as fading, Doppler, multipath, and jamming, which further complicates the ability to replicate such environments in a controlled laboratory setting. In this paper, we evaluate a previously developed Digital Wireless Channel Emulator (DWCE) by comparing field test results with data collected in an emulated environment for a 29 node tactical MANET. We present our approach for obtaining relevant metrics from the field and describe our methodology for comparison from both a qualitative and quantitative perspective.